Guidance navigation: support algorithms for grasping learning situations in unrestricted CSCL

Shoichi Nakamura, Kazuhiko Sato, Y. Miyadera, A. Koyama, Zixue Cheng
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Abstract

Recently, learning activities adopting web documents as learning materials have become quite prosperous with the rapid developments of network environment. This change has brought about diversification of needs in learning. Therefore, development of novel learning styles, which can satisfy various needs based on each learner's interests, knowledge, and so on, is strongly demanded. In this research, a synthetic environment for supporting novel learning styles has been developed.This paper mainly describes algorithms for supporting instructors to grasp learning situation, which is quite important for effective guidance. Specifically, algorithms for constructing valuable support knowledge based on visualization of learning information are developed. Algorithms for creating guidance navigation, which manages each instructor's guidance styles and assists his selecting support knowledge, are also developed. Finally, the effectiveness of developed support algorithms has been shown by experiments.
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引导导航:在无限制CSCL中掌握学习情况的支持算法
近年来,随着网络环境的快速发展,以网络文档为学习材料的学习活动变得十分活跃。这种变化带来了学习需求的多样化。因此,强烈要求开发新颖的学习方式,以满足每个学习者的兴趣、知识等方面的各种需求。在本研究中,开发了一个支持新型学习方式的综合环境。本文主要描述了支持教师掌握学习情境的算法,这对于有效的指导是非常重要的。具体而言,基于学习信息的可视化,提出了构建有价值支持知识的算法。本文还开发了创建指导导航的算法,该算法可以管理每个教师的指导风格并帮助他选择支持知识。最后,通过实验验证了所开发的支持算法的有效性。
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